Book Image

Mastering Kibana 6.x

Book Image

Mastering Kibana 6.x

Overview of this book

Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana’s Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities.
Table of Contents (21 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Data source functions


Kibana Timelion provides us with the option to load the data into the graph. We have already discussed one data source, function.es(), which loads data from Elasticsearch. Apart from .es(), Timelion also provides us with some more data sources from whuch we can load the data.

Some of them are World Bank and Quandl. We will now discuss the sources one by one.

Elasticsearch

The first data source is Elasticsearch and it is applied by default when we open the Timelion interface on Kibana. It is denoted with the .es() function and provides a lot of functionalities through which we can play around on the Elasticsearch index data.

The .es() function has different parameters, which we have already discussed such as split, which splits the series plot by the value of a specific field and the metric parameter to control the calculation of the y axis value. We can specify additional metrics aggregation, for example, avg, min, or max:

.es(metric='max:system.memory.used.bytes').label...